# 混合使用 match 和近似匹配实现召回率与精准度的平衡
# 什么是召回率与精准度
召回率
比如你搜索一个 java spark，总共有 100 个 doc，能返回多少个 doc作为结果，就是召回率（recall）
精准度
比如你搜索一个 java spark，能不能尽可能让包含 java spark 或者是 java 和 spark 离的很近的 doc， 排在最前面，这个就是精准度（precision）
直接用 match_phrase 短语搜索（包括 proximity match），会导致必须所有 term 都在 doc field 中出现， 而且距离在 slop 限定范围内，才能匹配上，如果某一个 doc 可能就是有某个 term 没有包含，那么就无法作为结果返回
如：
java spark --> hello world java --> 就不能返回了
java spark --> hello world, java spark --> 才可以返回
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近似匹配的时候，召回率比较低，精准度太高了。
那么怎么才能达到：召回率高，精准度高的排在最前面呢？ 也就是说希望上面两条数据都返回，但是第二条排在前面
这里就可以混合使用 match 与近似匹配来达到这个效果
# 混合使用 match 与近似匹配
GET /forum/article/_search
{
"query": {
"bool": {
"must": [
{"match": {
"content": "java spark"
}}
],
"should": [
{"match_phrase": {
"content": {
"query": "java spark",
"slop": 50
}
}}
]
}
}
}
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响应结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 5,
"max_score": 2.5593896,
"hits": [
{
"_index": "forum",
"_type": "article",
"_id": "7",
"_score": 2.5593896,
"_source": {
"content": "java spark are very related, because scala is spark's programming language and scala is also based on jvm like java."
}
},
{
"_index": "forum",
"_type": "article",
"_id": "6",
"_score": 1.3154804,
"_source": {
"content": "java is my favourite programming language, and I also think spark is a very good big data system."
}
},
{
"_index": "forum",
"_type": "article",
"_id": "8",
"_score": 0.63663185,
"_source": {
"content": "java are spark very related, because scala is spark's programming language and scala is also based on jvm like java."
}
},
{
"_index": "forum",
"_type": "article",
"_id": "2",
"_score": 0.5099718,
"_source": {
"articleID": "KDKE-B-9947-#kL5",
"userID": 1,
"hidden": false,
"postDate": "2017-01-02",
"tag": [
"java"
],
"tag_cnt": 1,
"view_cnt": 50,
"title": "this is java blog",
"content": "i think java is the best programming language",
"sub_title": "learned a lot of course",
"author_first_name": "Smith",
"author_last_name": "Williams",
"new_author_last_name": "Williams",
"new_author_first_name": "Smith"
}
},
{
"_index": "forum",
"_type": "article",
"_id": "5",
"_score": 0.42019215,
"_source": {
"articleID": "DHJK-B-1395-#Ky5",
"userID": 3,
"hidden": false,
"postDate": "2019-01-28",
"tag": [
"elasticsearch"
],
"tag_cnt": 1,
"view_cnt": 10,
"title": "this is spark blog",
"content": "spark is best big data solution based on scala ,an programming language similar to java",
"sub_title": "haha, hello world",
"author_first_name": "Tonny",
"author_last_name": "Peter Smith",
"new_author_last_name": "Peter Smith",
"new_author_first_name": "Tonny"
}
}
]
}
}
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可以看到匹配上的都排在前面了，如果不使用 slop , id=2 的（只包含了 java） 会比部分都包含的 doc 得分高
match：提高了召回率
只要包含了 java 或者 spark 其中一个词的都符合结果
match_phrase 提高了精准度
使用 should 符合 match_phrase 条件的将会使 doc 的得分增加， 使用 slop 进一步提高召回率 两步相加召回率和得分都提高了